Breast cancer is a leading cause of malignancies in women, resulting in almost 200,000 new cases every year. In approximately one third of breast cancer patients, malignant cells spread to distant organs and cause metastatic tumors. Tumor progression, metastatic spread and patient prognosis depends on proteins present in cancerous cells. A number of proteins whose over-activation and impaired down-regulation have been implicated in these processes have been identified by recent studies. For example, over-expression of cell surface proteins - EGFR and ERBB2 (her2-neu) is correlated with a more aggressive breast cancer phenotype and a poor patient prognosis. In addition, during development of drug resistance, breast cancer cells over-express several cell surface proteins such as FGFR3. Therefore, analysis of cell surface proteins provides an excellent opportunity to diagnose breast cancer and predict prognosis and treatment outcomes. However, technologies for highly sensitive and specific multiplexed analysis of cell surface proteins at the single cell level are limited. In this project, we propose to further develop a novel technology for the analysis of as many as 30 cell surface proteins at a single cell level to achieve accurate breast cancer diagnosis, and predict therapeutic response and patient outcome rapidly and at a low cost.